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Model Summary Bar Chart

📊 What is this?

Model Summary tells you the model's indicators in text and numbers; the Model Summary Bar Chart takes the two most critical of them—— R² and Q²——and plots them as side-by-side bars, so that you can see the gap at a glance.

It is best at exposing one problem: overfitting.


🧐 How to read?

The chart shows a bar comparison of R² and Q²:

IndicatorMeaningExpectation
The model's ability to explain the training dataThe higher the better
The model's ability to predict unseen dataThe higher the better

The core reading is to look at "how much the two bars differ":

PatternDiagnosis
R² and Q² keep pace with each other✅ Healthy model, fitting ability matches generalization ability
R² is clearly higher than Q²⚠️ Overfitting——the model has memorized the noise as well
Both bars are very short⚠️ Underfitting——the wrong variables were chosen, or the relationship is inherently weak
Q² is negative or close to 0❌ The model has no predictive value

💡 Rule of thumb: R² - Q² < 0.2 is usually acceptable; once the gap exceeds 0.3, you need to be on guard.


🛠️ How to use?

  1. As the first health check of the model: after Fit is complete, drag this chart out first and glance at the bar heights
  2. Verify the cleaning effect: look once before and after deleting data——if the Q² bar has clearly grown taller, the points you removed were real noise
  3. Help decide the number of components: observe repeatedly together with C+1 / C-1 to find the component count where the gap between R² and Q² is smallest

Switching indicator type

The chart supports choosing the indicator type to display: R² only, Q² only, or a comparison of both.


🎯 Division of labor with "Model Summary"

ChartPresentationSuitable scenario
Model SummaryComplete indicator listWhen you need to see all indicators, the optimal component count, and CV details
Model Summary Bar ChartR² / Q² bar comparisonQuickly judge whether overfitting occurs, good for putting into reports

💡 Use the bar chart for reporting, use the summary table for troubleshooting——the bar chart has stronger visual impact, and non-technical colleagues can also see at a glance that "the two bars differ by this much, so there is a problem".

Let data speak, make decisions simpler.